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The Evolution of Cloud Computing in ATLAS
The ATLAS experiment has successfully incorporated cloud computing technology and cloud resources into its primarily grid-based model of distributed computing. Cloud R&D activities continue to mature and transition into stable production systems, while ongoing evolutionary changes are still need...
Autores principales: | , , , , , , , , , , , , , , |
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Lenguaje: | eng |
Publicado: |
2015
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Materias: | |
Acceso en línea: | https://dx.doi.org/10.1088/1742-6596/664/2/022038 http://cds.cern.ch/record/2016817 |
_version_ | 1780946709352808448 |
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author | Taylor, Ryan P Berghaus, Frank Brasolin, Franco Cordeiro, Cristovao Desmarais, Ron Field, Laurence Gable, Ian Giordano, Domenico Di Girolamo, Alessandro Hover, John Leblanc, Matthew Edgar Love, Peter Paterson, Michael Sobie, Randall Zaytsev, Alexandr |
author_facet | Taylor, Ryan P Berghaus, Frank Brasolin, Franco Cordeiro, Cristovao Desmarais, Ron Field, Laurence Gable, Ian Giordano, Domenico Di Girolamo, Alessandro Hover, John Leblanc, Matthew Edgar Love, Peter Paterson, Michael Sobie, Randall Zaytsev, Alexandr |
author_sort | Taylor, Ryan P |
collection | CERN |
description | The ATLAS experiment has successfully incorporated cloud computing technology and cloud resources into its primarily grid-based model of distributed computing. Cloud R&D activities continue to mature and transition into stable production systems, while ongoing evolutionary changes are still needed to adapt and refine the approaches used, in response to changes in prevailing cloud technology. In addition, completely new developments are needed to handle emerging requirements. This paper describes the overall evolution of cloud computing in ATLAS. The current status of the virtual machine (VM) management systems used for harnessing infrastructure as a service (IaaS) resources are discussed. Monitoring and accounting systems tailored for clouds are needed to complete the integration of cloud resources within ATLAS' distributed computing framework. We are developing and deploying new solutions to address the challenge of operation in a geographically distributed multi-cloud scenario, including a system for managing VM images across multiple clouds, a system for dynamic location-based discovery of caching proxy servers, and the usage of a data federation to unify the worldwide grid of storage elements into a single namespace and access point. The usage of the experiment's high level trigger (HLT) farm for Monte Carlo production, in a specialized cloud environment, is presented. Finally, we evaluate and compare the performance of commercial clouds using several benchmarks. |
id | cern-2016817 |
institution | Organización Europea para la Investigación Nuclear |
language | eng |
publishDate | 2015 |
record_format | invenio |
spelling | cern-20168172022-08-10T12:55:37Zdoi:10.1088/1742-6596/664/2/022038http://cds.cern.ch/record/2016817engTaylor, Ryan PBerghaus, FrankBrasolin, FrancoCordeiro, CristovaoDesmarais, RonField, LaurenceGable, IanGiordano, DomenicoDi Girolamo, AlessandroHover, JohnLeblanc, Matthew EdgarLove, PeterPaterson, MichaelSobie, RandallZaytsev, AlexandrThe Evolution of Cloud Computing in ATLASParticle Physics - ExperimentComputing and ComputersThe ATLAS experiment has successfully incorporated cloud computing technology and cloud resources into its primarily grid-based model of distributed computing. Cloud R&D activities continue to mature and transition into stable production systems, while ongoing evolutionary changes are still needed to adapt and refine the approaches used, in response to changes in prevailing cloud technology. In addition, completely new developments are needed to handle emerging requirements. This paper describes the overall evolution of cloud computing in ATLAS. The current status of the virtual machine (VM) management systems used for harnessing infrastructure as a service (IaaS) resources are discussed. Monitoring and accounting systems tailored for clouds are needed to complete the integration of cloud resources within ATLAS' distributed computing framework. We are developing and deploying new solutions to address the challenge of operation in a geographically distributed multi-cloud scenario, including a system for managing VM images across multiple clouds, a system for dynamic location-based discovery of caching proxy servers, and the usage of a data federation to unify the worldwide grid of storage elements into a single namespace and access point. The usage of the experiment's high level trigger (HLT) farm for Monte Carlo production, in a specialized cloud environment, is presented. Finally, we evaluate and compare the performance of commercial clouds using several benchmarks.ATL-SOFT-PROC-2015-049oai:cds.cern.ch:20168172015-05-18 |
spellingShingle | Particle Physics - Experiment Computing and Computers Taylor, Ryan P Berghaus, Frank Brasolin, Franco Cordeiro, Cristovao Desmarais, Ron Field, Laurence Gable, Ian Giordano, Domenico Di Girolamo, Alessandro Hover, John Leblanc, Matthew Edgar Love, Peter Paterson, Michael Sobie, Randall Zaytsev, Alexandr The Evolution of Cloud Computing in ATLAS |
title | The Evolution of Cloud Computing in ATLAS |
title_full | The Evolution of Cloud Computing in ATLAS |
title_fullStr | The Evolution of Cloud Computing in ATLAS |
title_full_unstemmed | The Evolution of Cloud Computing in ATLAS |
title_short | The Evolution of Cloud Computing in ATLAS |
title_sort | evolution of cloud computing in atlas |
topic | Particle Physics - Experiment Computing and Computers |
url | https://dx.doi.org/10.1088/1742-6596/664/2/022038 http://cds.cern.ch/record/2016817 |
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